Digital Signal Processing (DSP)

What is the project about?

This project consists of two key components:

Lab Report: Frequency Domain Analysis & Filter Designs

• Implementation of Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) filters.
• Designed Butterworth and Chebyshev filters for signal filtering.
• Developed high-pass and band-stop filters for noise removal.
• Simulated and analyzed frequency responses in MATLAB.

Individual Assignment: Audio Processing Application for Speech Enhancement

• Developed a MATLAB App Designer application to enhance speech signals.
• Integrated Kalman Filter, Spectral Subtraction, Butterworth, and Chebyshev filters.
• Allowed users to record, load, and filter audio in real-time.
• Focused on removing noise types such as white noise, Gaussian noise, pink noise, and Brownian noise.

Why was it created?

• To explore DSP filtering techniques for noise removal and signal enhancement.
• To develop a real-world audio processing tool for speech improvement.
• To implement MATLAB-based DSP algorithms using App Designer.

How does it work?

Signal Filtering & Analysis

• The system applies IIR and FIR filters to process input signals.
• Different filters are tested for frequency response analysis.

Audio Processing Application

• Users can record or upload audio files for processing.
• The app applies selected filters to remove noise.
• Real-time feedback is provided on the signal improvement.

Speech Enhancement Techniques

• Kalman Filter: Estimates and removes noise dynamically.
• Spectral Subtraction: Reduces background noise in speech signals.
• Butterworth and Chebyshev Filters: Improve audio clarity.